Computer-Assisted Learning Based on Cumulative Vocabularies, Conceptual Networks and Wikipedia Linkage

Lauri Lahti

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

In this doctoral dissertation we propose new methods and frameworks for computer-assisted learning based on self-designed and self-implemented software prototypes supplied with user testing. Motivated by previous research identifying possibly similar scale-free small-world properties in Wikipedia online encyclopedia, social networks and human brain networks, we suggest that collaboratively generated knowledge structures of Wikipedia can be used to support learning. After reviewing background of computer-assisted and collaborative network-based learning we introduce using lists of concepts and conceptual relationships generated by students and comparison through rankings. We propose supporting collaborator roles in a collaborative learning environment relying on text-based discussion chains illustrated cumulatively as concept maps. Next, we propose guided generation of concept maps from the hyperlink network of Wikipedia. Then, we propose generating personalized learning paths from Wikipedia by following hyperlinks between articles based on various rankings of the statistics of the articles. We extend this to manage parallel ranking lists, branching structures and different temporal versions of Wikipedia articles. Next, we propose a wiki environment representing pedagogic knowledge with a collaboratively edited collection of concept maps enabling to analyze maturing of knowledge and to define pedagogically motivated learning paths and educational games. Then, we propose three kinds of learning concept networks, representing the learner's knowledge, the learning context and the learning objective, and letting the learner to explore them with ranking-based routings based on the shortest hyperlink chains between corresponding Wikipedia articles. We extend this by proposing pedagogic conceptual networks generated based on the shortest connecting paths in the hyperlink network of Wikipedia and traversing hyperlinks with a tailored variation and repetition based on theory of spaced learning supplied with visualizations. Then, we propose cumulative conceptual networks based on the hyperlink network of Wikipedia connecting concepts of the vocabulary about the current learning topic and alternating the distribution of traversable hyperlinks letting the learner to explore the shortest paths between the concepts of the vocabulary. We measured learning effects for recall of selected and shown hyperlinked concepts and recall for shown hyperlinked concepts forming the shortest paths. We also estimated conceptual networks for alternative language ability levels and contrasted them with a review about measures of human learning process and representation of knowledge.
Translated title of the contributionTietokoneavusteinen oppiminen perustuen karttuviin sanastoihin, käsiteverkostoihin ja Wikipedian linkitykseen
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Tarhio, Jorma, Supervising Professor
Publisher
Print ISBNs978-952-60-6163-4
Electronic ISBNs978-952-60-6164-1
Publication statusPublished - 2015
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • intelligent tutoring
  • adaptive hypermedia
  • Wikipedia
  • learning environment
  • language acquisition
  • associative network
  • concept map
  • wiki
  • spaced learning

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